package com.at.bigdata.spark.streaming

import com.at.bigdata.spark.util.JDBCUtil
import org.apache.kafka.clients.consumer.ConsumerConfig
import org.apache.spark.SparkConf
import org.apache.spark.streaming.kafka010.{ConsumerStrategies, KafkaUtils, LocationStrategies}
import org.apache.spark.streaming.{Seconds, StreamingContext}

import java.text.SimpleDateFormat
import java.util.Date
import scala.collection.mutable.ListBuffer

/**
 *
 * @author cdhuangchao3
 * @date 2023/5/29 9:24 PM
 */
object SparkStreaming12_Req2 {

  def main(args: Array[String]): Unit = {
    // 创建环境
    // 创建时，需要传递2个参数：
    //    param： 环境配置
    val sc = new SparkConf().setMaster("local[*]").setAppName("operator")
    //    param2: 采集周期
    val ssc = new StreamingContext(sc, Seconds(3))

    val kafkaPara = Map[String, Object](
      ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG -> "linux1:9092,linux2:9092,linux3:9092",
      ConsumerConfig.GROUP_ID_CONFIG -> "at",
      ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG -> "org.apache.kafka.common.serialization.StringDeserializer",
      ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG -> "org.apache.kafka.common.serialization.StringDeserializer"
    )

    val kafkaDataDS = KafkaUtils.createDirectStream[String, String](
      ssc,
      LocationStrategies.PreferConsistent,
      ConsumerStrategies.Subscribe[String, String](Set("at"), kafkaPara)
    )

    val adClickData = kafkaDataDS.map(
      kafkaData => {
        val data = kafkaData.value()
        val datas = data.split(" ")
        AdClickData(datas(0), datas(1), datas(2), datas(3), datas(4))
      }
    )
    val reduceDS = adClickData.map(
      data => {
        val sdf = new SimpleDateFormat("yyyy-MM-dd")
        val day = sdf.format(new Date(data.ts.toLong))
        val area = data.area
        val city = data.city
        val ad = data.ad
        ((day, area, city, ad), 1)
      }
    ).reduceByKey(_ + _)

    reduceDS.foreachRDD(
      rdd => {
        rdd.foreachPartition(
          iter => {
            val conn = JDBCUtil.getConn()
            val sql =
              """
                |insert into area_city_ad_count(dt,area,city,adid,count) values(?,?,?,?)
                | on duplicate key
                | update count = ?
                |""".stripMargin
            iter.foreach {
              case ((day, area, city, ad), sum) => {
                JDBCUtil.executeUpdate(conn, sql, Array(day, area, city, ad, sum, sum))
              }
            }
          }
        )
      }
    )

    // 1、启动采集器
    ssc.start()
    // 2、等待采集器的关闭
    ssc.awaitTermination()
  }

  // 广告点击数据
  case class AdClickData(ts: String, area: String, city: String, user: String, ad: String)
}
